Abstract
The smart grid provides a good chance for the application of demand response technology, which could improve the renewable energy consumption and system stability. This paper proposes a Fuzzy C-means based User Clustering Method for Demand Response Regulation. Fuzzy C-means clustering method is adopted to find the user set which has the closest load characteristics with the renewable energy generation. This user set has the best probability to consume renewable energy. Then, particle swarm algorithm is used to adjust the electric price, which could slightly change the electric consumption behavior of the above user set. Finally, a higher renewable energy consumption rate could be achieved under a stable and economical condition.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 40th Chinese Control Conference, CCC 2021 |
| Editors | Chen Peng, Jian Sun |
| Publisher | IEEE Computer Society |
| Pages | 5752-5757 |
| Number of pages | 6 |
| ISBN (Electronic) | 9789881563804 |
| DOIs | |
| Publication status | Published - 26 Jul 2021 |
| Event | 40th Chinese Control Conference, CCC 2021 - Shanghai, China Duration: 26 Jul 2021 → 28 Jul 2021 |
Publication series
| Name | Chinese Control Conference, CCC |
|---|---|
| Volume | 2021-July |
| ISSN (Print) | 1934-1768 |
| ISSN (Electronic) | 2161-2927 |
Conference
| Conference | 40th Chinese Control Conference, CCC 2021 |
|---|---|
| Country/Territory | China |
| City | Shanghai |
| Period | 26/07/21 → 28/07/21 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Curve Similarity
- Demand Response
- Fuzzy C-means clustering
- Particle Swarm Optimization
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